Deep learning in multi-object detection and tracking: state of the art
Object detection and tracking is one of the most important and challenging branches in
computer vision, and have been widely applied in various fields, such as health-care …
computer vision, and have been widely applied in various fields, such as health-care …
Object detection with deep learning: A review
Due to object detection's close relationship with video analysis and image understanding, it
has attracted much research attention in recent years. Traditional object detection methods …
has attracted much research attention in recent years. Traditional object detection methods …
CCTSDB 2021: a more comprehensive traffic sign detection benchmark
J Zhang, X Zou, LD Kuang, J Wang… - Human-centric …, 2022 - centaur.reading.ac.uk
Traffic signs are one of the most important information that guide cars to travel, and the
detection of traffic signs is an important component of autonomous driving and intelligent …
detection of traffic signs is an important component of autonomous driving and intelligent …
Specificity-preserving RGB-D saliency detection
RGB-D saliency detection has attracted increasing attention, due to its effectiveness and the
fact that depth cues can now be conveniently captured. Existing works often focus on …
fact that depth cues can now be conveniently captured. Existing works often focus on …
Hierarchical alternate interaction network for RGB-D salient object detection
Existing RGB-D Salient Object Detection (SOD) methods take advantage of depth cues to
improve the detection accuracy, while pay insufficient attention to the quality of depth …
improve the detection accuracy, while pay insufficient attention to the quality of depth …
Two-layer federated learning with heterogeneous model aggregation for 6g supported internet of vehicles
The vision of the upcoming 6G technologies that have fast data rate, low latency, and ultra-
dense network, draws great attentions to the Internet of Vehicles (IoV) and Vehicle-to …
dense network, draws great attentions to the Internet of Vehicles (IoV) and Vehicle-to …
Hyperspectral image super-resolution via deep spatiospectral attention convolutional neural networks
Hyperspectral images (HSIs) are of crucial importance in order to better understand features
from a large number of spectral channels. Restricted by its inner imaging mechanism, the …
from a large number of spectral channels. Restricted by its inner imaging mechanism, the …
Weakly-supervised semantic segmentation by iteratively mining common object features
Weakly-supervised semantic segmentation under image tags supervision is a challenging
task as it directly associates high-level semantic to low-level appearance. To bridge this gap …
task as it directly associates high-level semantic to low-level appearance. To bridge this gap …
A mutual learning method for salient object detection with intertwined multi-supervision
Though deep learning techniques have made great progress in salient object detection
recently, the predicted saliency maps still suffer from incomplete predictions due to the …
recently, the predicted saliency maps still suffer from incomplete predictions due to the …
EDN: Salient object detection via extremely-downsampled network
Recent progress on salient object detection (SOD) mainly benefits from multi-scale learning,
where the high-level and low-level features collaborate in locating salient objects and …
where the high-level and low-level features collaborate in locating salient objects and …